AI/ML - Data Engineer (NLP/Speech), Siri and Information Intelligence

Apple
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Graduate Machine Learning and AI Engineer

Freelance Spatial AI and Machine Learning Consultant

Machine Learning Engineer

Data Science Practitioner

Data Science Practitioner

Data Engineer

Summary:
Play a part in the next revolution in human-computer interaction. Contribute to a product that is redefining mobile computing. Create groundbreaking technology for large scale systems, natural language, big data, and artificial intelligence. And work with the people who created the intelligent assistant that helps millions of people get things done — just by asking. Join the Siri Response / Text-to-Speech (TTS) team at Apple. Our team is looking for exceptional data engineers passionate about delivering delightful customer experiences with Siri voices. As Data Engineer (NLP/Speech), you'll work on building and maintaining text and speech datasets, processes and workflows for our TTS systems.
Key Qualifications:
5+ years’ industry experience processing large-scale text/speech datasets for ML applicationsStrong expertise in Python, (NoSQL) databases, cloud-based data technologies, and working with large datasets and pipelinesExperience in tooling and streamlining workflows in complex processesHighly-motivated, creative, organized and a strong problem solverOutstanding spoken and written communication skills
Description:
Apple is hiring data engineers for the Siri Response / Text-to-Speech (TTS) team. You'll be working at the frontier of AI, processing massive amounts of speech and text data for our TTS systems. You'll work closely with fellow engineers to gather and integrate new speech and text data into our repositories, transforming raw data into formats usable for TTS model training, and making datasets available to partner teams in Apple to power Siri's voice. Your responsibilities will include: * Collect and centralize data from various sources, working with internal privacy, legal and modeling teams* Build processes and workflows that support data transformation for TTS systems (e.g. audio processing and text annotation), based on the needs and requirements of modeling teams* Provide datasets to partner teams, managing access or usage control* Create dashboard for interactive data exploration* Develop tools and tests to ensure quality and help diagnose issues* Perform analysis on external and internal processes and data to identify opportunities for improvement* Develop prototype ML models utilizing in-house toolkits If this sounds like you, we'd love to hear from you!
Additional Requirements:
* Experience in working with natural language data, lexical resources, corpora, NLP algorithms and tools is a plus* Experience in machine learning, natural language processing, machine translation or text-to-speech is a plus* Knowledge of one or more foreign languages is a plus

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.